CPT-L to Improve Outcomes for Individuals With HIV and PTSD: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for CPT-L to Improve Outcomes for Individuals With HIV and PTSD (NCT05275842), a randomized na study. The primary outcome is Percent of Completed Participants.

2. Clinical Question

The study was designed to adapt and examine the acceptability and feasibility of an integrated PTSD and adherence intervention in an HIV clinic. The registry’s brief summary describes the approach as adapting Cognitive Processing Therapy, which it says has reduced other HIV transmission behavior such as sexual risk, as a strategy to improve HIV outcomes in this population. The posted primary endpoint, however, is completion of the study protocol. It does not directly measure acceptability, adherence, PTSD symptoms, or HIV outcomes.

The study also lists PTSD symptom scales, viral suppression, and medication pill count or compliance among its secondary outcomes. These outcomes address different questions: symptom measures describe PTSD-related scores, viral suppression records an HIV outcome, and pill count or compliance concerns medication-taking. Their measurement timing and available results differ, so they should not be treated as interchangeable evidence about the primary feasibility question.

3. Trial Design

The registry describes a randomized, parallel-group study with single masking. It lists the phase as NA and the status as completed. The study was sponsored by the Medical University of South Carolina. Its recorded start date is 2022-07-13, and its primary completion date is 2024-08-30.

Participants were assigned to CPT-L [Group A] or Lifesteps [Group B]. The registry lists 20 participants in Group A and 21 in Group B. Both interventions are classified as behavioral. Although masking is recorded as single, the identity of the masked party is not reported in the registry record. The method used to generate the random allocation sequence and the procedure used to conceal allocation are also not reported in the registry record.

The primary endpoint concerns completion at the 6-week end-of-study visit. The registry lists CAPS-5 and PCL-5 as collected at baseline and the 6-week end-of-study treatment visit, while viral suppression is listed for 6 months after enrollment. Medication pill count or compliance appears in the secondary-outcome list, but its measurement timing and result are not reported in the registry record. These distinct time points matter: a measure collected at the end of treatment does not answer the same time-specific question as an outcome assessed later.

Enrollment and the numbers contributing to particular outcome summaries are not identical. For example, the posted PTSD summaries have smaller group counts than the enrollment counts, and the viral suppression summaries have their own group counts. The reasons for those differences, including whether they reflect missing measurements, eligibility for a particular analysis, or another explanation, are not reported in the registry record. The analysis population and missing-data procedures are likewise not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Screened population

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: Baseline Population is denoted as all randomized participants

6. Primary Endpoint

The registry lists the primary outcome as Percent of Completed Participants, measured over 6-week end of study visit.

The primary endpoint is titled “Percent of Completed Participants.” Its description defines it as the percentage of participants who were enrolled and completed the study protocol, assessed at the 6-week end-of-study visit. The registry reports 12 participants for CPT-L [Group A] and 17 for Lifesteps [Group B], with group counts of 20 and 21, respectively. The posted comparison gives an unadjusted p-value of 0.141. The estimated risk difference is positive for Lifesteps relative to CPT-L, while its confidence interval includes no difference.

Completion is used in feasibility work because it indicates whether participants remain engaged through the protocol’s specified endpoint. It is a process measure: it describes study participation and completion, not whether PTSD symptoms changed or whether HIV outcomes improved. In general, a completion endpoint can help inform whether procedures and follow-up are workable, but it does not by itself establish why participants did or did not complete the study.

The record does not give a separate definition of what counted as completing every protocol component, nor does it describe how partial completion or missed visits were classified. Those details are important for interpreting a completion measure because different operational definitions can produce different classifications. The endpoint should therefore be read according to the registry’s stated definition, without assuming additional completion rules.

7. Results Posted in the Registry

• Lifesteps [Group B]: 81.0% (17/21) versus 60.0% (12/20) on control; risk difference 21.0 percentage points (95% CI -6.3 to 48.2), risk ratio 1.35 (0.89–2.04); unadjusted two-proportion z-test p = 0.141.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Clinician Administered PTSD Scale for DSM-5 (CAPS-5)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Lifesteps [Group B]: mean 29.40 versus 18.50 on control; difference 10.90 (95% CI -0.32 to 22.12), standardized effect d = 0.75; z-test p = 0.057.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Lifesteps [Group B] and the control. The interval gives the range of effects that remain compatible with the data.

PTSD Checklist for DSM-5 (PCL-5)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Lifesteps [Group B]: mean 33.70 versus 18.50 on control; difference 15.20 (95% CI 0.69 to 29.71), standardized effect d = 0.83; z-test p = 0.040.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Lifesteps [Group B] than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Number of Patients With Suppressed Viral Load

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Lifesteps [Group B]: 76.9% (10/13) versus 93.3% (14/15) on control; risk difference -16.4 percentage points (95% CI -42.6 to 9.7), risk ratio 0.82 (0.59–1.14); unadjusted two-proportion z-test p = 0.216.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Lifesteps [Group B] and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the questions beyond protocol completion. The PTSD symptom measures describe scores at the end-of-study treatment visit, while viral suppression is recorded at 6 months after enrollment. Medication pill count or compliance is also listed, but a result for that measure is not reported in the registry record.

Across the posted symptom summaries, mean scores are lower in CPT-L than in Lifesteps. The two comparisons do not have the same uncertainty: the CAPS-5 interval includes zero, whereas the PCL-5 interval does not. The viral-suppression comparison points in the opposite direction from the primary completion comparison, but its interval includes zero. These broad patterns do not constitute a single consistent result across outcome types, and the measures address different aspects of the intervention.

The primary outcome is completion, so the secondary results do not replace or redefine the primary finding. At most, they provide additional descriptive information about symptom scores and a later HIV outcome. The record does not report a unified analysis linking completion to these outcomes or explain how the different outcome denominators arose.

Secondary findings carry less weight when they are unadjusted and considered among several outcomes. Testing multiple outcomes creates more opportunities for a result to appear notable by chance. The registry does not report a multiplicity adjustment or a prespecified hierarchy for interpreting secondary outcomes. Accordingly, the p-value for PCL-5 should not be isolated from the wider pattern of uncertainty, and none of the secondary comparisons should be treated as definitive evidence on its own.

These outcomes may be useful for generating hypotheses and planning future research. Stronger conclusions would require clearly reported measurement definitions, analysis populations, missing-data handling, and an analysis plan that explains how the primary and secondary questions relate.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Clinician Administered PTSD Scale for DSM-5 (CAPS-5)
• PTSD Checklist for DSM-5 (PCL-5)
• Number of Patients With Suppressed Viral Load
• Medication Pill Count / Compliance

9. Statistical Interpretation

10. Statistical Methods Explained

What does the risk difference represent?

A risk difference compares the proportion with an outcome in one group against the proportion in another. For the primary endpoint, the posted comparison is Lifesteps relative to CPT-L. A positive estimate means the observed completion proportion is higher in Lifesteps; a negative estimate would mean it is lower. The estimate is an absolute difference in proportions, not a relative percentage change. Its confidence interval describes a range of values compatible with the data under the calculation’s assumptions. Because the primary interval spans zero, the posted data are compatible with no between-group difference as well as with differences in either direction.

For binary outcomes, counts and denominators are essential context. The primary completion results are reported with group counts, while viral suppression has its own outcome-specific counts. Those outcome denominators should not be assumed to equal enrollment or one another. The registry does not explain why the outcome counts differ.

How should the mean differences be read?

CAPS-5 and PCL-5 are reported as means with standard deviations, and the posted comparisons are mean differences for Lifesteps relative to CPT-L. A positive mean difference indicates a higher observed average in Lifesteps. For CAPS-5, the posted means are 18.5 for CPT-L and 29.4 for Lifesteps, with a mean difference of 10.9. For PCL-5, the means are 18.5 and 33.7, respectively, with a mean difference of 15.2. The registry gives each measure’s standard deviations and an unadjusted comparison.

A mean difference retains the scale’s units, unlike a standardized effect size. Interpreting whether a particular score is clinically important requires information about scale interpretation and meaningful-change thresholds; those thresholds are not reported in the registry record. The means are also summaries of the participants with recorded values, not necessarily of every enrolled participant.

What does a p-value say?

A p-value measures how compatible the observed data are with a specified null model of no group difference, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. The posted p-values are unadjusted. Their interpretation does not account for the fact that multiple outcomes are considered, and the registry does not report a multiplicity plan.

The primary p-value is 0.141. This is not a declaration that the groups are identical. It means the posted primary comparison does not provide strong evidence against the null model under the unadjusted test. The uncertainty interval is also relevant: it indicates that the estimate is not precise enough to rule out a range of possible differences.

Why does uncertainty matter?

Confidence intervals communicate uncertainty around an estimated effect. A narrow interval indicates greater precision than a wide one, while an interval crossing zero for a difference is compatible with no difference under the interval’s assumptions. It does not prove that the true effect is exactly zero. Conversely, an interval that does not cross zero does not establish that an effect is clinically important or free from bias. The registry’s intervals should be read alongside group counts, outcome definitions, and the unadjusted nature of the comparisons.

In general, small studies tend to yield less precise estimates, particularly when outcomes are binary and event counts are limited. Random variation can have a substantial influence on the estimated proportions. This is relevant to a feasibility study: estimates can be informative for planning while still having considerable uncertainty. The available record does not report a formal sample-size justification for the original trial.

Why can over-dispersion matter?

General statistical explanation: for count outcomes, a model that assumes a particular mean-variance relationship can be too restrictive if the data vary more than that model expects. This is called over-dispersion. In that situation, conventional standard errors may be too small, confidence intervals may be too narrow, and tests may appear more decisive than warranted. The posted primary and viral outcomes are presented as participant counts with binary comparisons, not as over-dispersed count-model analyses. The registry does not report an over-dispersion assessment or a model-based adjustment.

What analysis details are available?

The registry gives the outcome summaries and unadjusted comparisons but does not list reported secondary analyses. It does not report the statistical model, whether the PTSD comparisons use baseline-adjusted or change-from-baseline values, or the handling of missing observations. It also does not identify the precise population used for each analysis. Without those details, the summaries cannot be assumed to represent an intention-to-treat analysis or a prespecified adjusted analysis.

The trial is marked randomized, but that designation alone does not resolve these analytic questions. Randomization supports comparison of assigned groups when implemented and analyzed appropriately, while departures from assignment, missing outcomes, small group counts, and selective reporting can still affect interpretation. The registry record does not provide enough detail to assess those features fully.

11. Confidence Intervals and Precision

Precision is the degree of uncertainty around an estimated group difference. The primary completion interval is wide enough to include zero, so the data do not pin down the direction of the underlying difference. The point estimate is positive for Lifesteps relative to CPT-L, but a point estimate is only one value within a broader range of uncertainty. The primary p-value of 0.141 is consistent with that cautious reading.

The secondary comparisons also vary in precision. The CAPS-5 interval includes zero, while the PCL-5 interval does not; those distinctions should be read together with their unadjusted p-values and the fact that several outcomes are assessed. The viral-suppression interval includes zero. The registry reports no adjusted secondary analyses or multiplicity procedure that would account for examining multiple outcomes.

In general, an interval is not a guarantee that the true effect lies within its limits. It describes the uncertainty generated by a statistical procedure under assumptions about the data and analysis. A confidence interval crossing zero does not prove there is no effect, and an interval excluding zero does not by itself establish clinical importance. The sizes of the group counts and the outcome-specific denominators also matter: the posted counts differ across outcomes, and the reasons for that are not reported.

The study’s feasibility focus is important when reading precision. A small feasibility study can identify the range of estimates that may be plausible and can inform subsequent planning, but it may not provide precise estimates of effects. The registry record does not report a prespecified precision target or the original sample-size rationale, so the extent to which the observed uncertainty was anticipated is unknown.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participant counts per arm, not total event counts. They are illustrations based on the observed primary effect, rather than the original trial’s design assumptions. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is a stated fraction of the observed effect.

For planning at 100% of the observed primary effect, the illustration gives 74 participants per arm for 80% power and 98 participants per arm for 90% power. For planning at 75% of the observed effect, it gives 138 participants per arm for 80% power and 184 participants per arm for 90% power. For planning at 50% of the observed effect, it gives 324 participants per arm for 80% power and 433 participants per arm for 90% power.

In plain language, 80% power means that a study designed under the stated assumptions would have an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% column represents a higher chance of detecting that same specified effect, and therefore requires a larger planned group size in these illustrations. Smaller effects require more participants to distinguish them from random variation with a similar level of power.

These values are not observed power. They are planning illustrations derived from the observed effect, not evidence about the probability that this completed study detected an effect. The original trial’s sample-size assumptions and justification are not reported in the registry record.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.600; treatment proportion p₁ = 0.810; average p̄ = 0.705.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6451 = 1.2644.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6278 = 0.5284.
4. n = (1.2644 + 0.5284)² / (0.2095)² = 73.2, rounded up to 74 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.6                          # control proportion
p1 <- 0.80952380952381                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(5275842)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 74 (80% power), 98 (90% power)
 75% of observed effect: n per arm = 138 (80% power), 184 (90% power)
 50% of observed effect: n per arm = 324 (80% power), 433 (90% power)
power.prop.test: 73.2 
Simulated power at n = 74 per arm: 0.812 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry record does not report a plan for controlling multiplicity. This matters because the study includes a primary completion endpoint and several secondary outcomes, with more than one statistical comparison posted. When many outcomes are examined, the chance of at least one seemingly persuasive result can increase even if there is no true effect. Adjustment methods or a prespecified testing hierarchy can address that issue, but no such approach is reported in the registry record. The posted secondary p-values are unadjusted and should be treated as exploratory evidence rather than as a set of independent confirmatory tests.

Missing-data procedures are not reported in the registry record. The posted group counts differ by endpoint, including between enrollment and the PTSD and viral-suppression summaries. The record does not state whether participants missed visits, whether measurements were unavailable for other reasons, or how absent values were treated. It does not describe imputation, complete-case analysis, sensitivity analyses, or rules for defining a missing outcome. No explanation should be inferred from the differences in counts alone.

The analysis populations are also not reported in the registry record. It is not stated whether participants were analyzed according to randomized assignment, whether a per-protocol population was used, or whether other eligibility rules applied to individual outcomes. These distinctions matter because analyzing only participants with an observed measurement can produce a different comparison from an analysis that retains all randomized participants under a defined missing-data approach.

The record does identify random allocation, but it does not give the analysis plan needed to assess how allocation was handled after randomization. It also does not report interim analyses or stopping rules. These omissions limit assessment of selective analysis and the robustness of the posted comparisons. They do not establish that inappropriate methods were used; they mean the relevant details are not reported in the registry record.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

The serious-adverse-event record lists zero serious events in each group and zero deaths in each group. It also lists zero other adverse events in each group. The at-risk counts are 20 for CPT-L and 21 for Lifesteps for both serious and other adverse events.

These figures describe what is recorded in the registry; they do not demonstrate that no adverse experience occurred outside the categories or reporting procedures represented in the record. The registry does not provide serious-event terms, and no event terms are listed. It also does not describe the event collection method, duration of safety follow-up, severity definitions, or rules for attributing events to an intervention.

With a feasibility study and outcome-specific group counts of this size, a zero count should be interpreted as an absence of recorded events in the listed categories, not proof that an event is impossible or that risk is absent. The safety record is descriptive and does not support a broader comparative safety conclusion.

16. What the Result Does, and Does Not, Mean

The result shows that completion was recorded for 12 participants assigned to CPT-L and 17 assigned to Lifesteps, with group sizes of 20 and 21. The estimated risk difference points toward a higher completion proportion in Lifesteps, but the confidence interval includes zero and the unadjusted p-value is 0.141. The estimate is uncertain, and the posted comparison does not establish a clear difference between groups.

This finding does not mean that the groups are proven equivalent. A non-significant comparison can reflect limited precision as well as a small underlying difference. Nor does the result establish that either intervention is effective or ineffective for PTSD, medication adherence, or HIV outcomes. Completion is a feasibility measure, not a clinical outcome. Secondary measurements offer additional information, but their unadjusted nature and uncertainty require restraint.

The study is described as an adaptation and feasibility test of CPT-L in an HIV clinic. Its record can therefore be read as an early evaluation of whether participants completed a short study protocol and as a source of outcome estimates for future planning. It cannot, from these registry summaries alone, answer all questions about acceptability, feasibility of delivery, symptom change, adherence, or longer-term viral suppression.

Interpretation is also bounded by reporting gaps. The registry does not report the original sample-size rationale, statistical analysis plan, analysis populations, or missing-data methods. It does not explain the differences in outcome counts or give a result for medication pill count or compliance. These gaps make it harder to determine how complete the comparisons are and how they should be weighted.

The posted results should therefore be treated as estimates from a completed randomized study, not as a final clinical conclusion. The confidence intervals, outcome definitions, and analysis details matter alongside the point estimates. Conclusions about broader populations or clinical benefit are not established by this record.

17. Why This Trial Matters Statistically

This trial illustrates why feasibility outcomes and clinical outcomes need to be kept distinct. Completion is directly relevant to whether participants reached the study endpoint, but it is not interchangeable with a change in PTSD symptoms or an HIV outcome. Separating these questions prevents an observed completion pattern from being overinterpreted as a treatment effect on health.

It also illustrates the role of precision in a randomized comparison. The primary estimate points in one direction, but its interval includes no difference. Reporting the estimate with its uncertainty is more informative than relying on a binary significant-or-not-significant label. The secondary comparisons further demonstrate that outcomes can have differing directions and degrees of uncertainty within the same study.

For biostatistical practice, the record highlights the value of transparent reporting about analysis populations, missing data, multiplicity, and sample-size rationale. These details are particularly important when multiple outcomes have different denominators and measurement times. Without them, readers can describe the posted estimates but have limited ability to assess robustness or reconstruct the intended inferential framework.

Finally, planning illustrations based on observed effects can help show how uncertain estimates translate into future study-size requirements. They are not evidence of power achieved by the completed trial. Distinguishing planning quantities from observed results helps avoid a common interpretive error and supports more realistic discussion of what a feasibility study can establish.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record leaves several trial-specific limitations unresolved. It does not report the original sample-size justification, so it is not possible to assess whether the planned enrollment was chosen to estimate completion with a target level of precision or for another reason. Planning values based on the observed effect are illustrative and do not supply that missing rationale.

Outcome counts differ across the primary, symptom, and viral-suppression summaries. The reasons are not reported, and there is no description of missing-data handling or analysis populations. This makes it difficult to determine whether the observed participants for each endpoint represent the randomized groups in a comparable way. Baseline characteristics and an assessment of group balance are not included in the record.

The registry identifies the study as single masked but does not state who was masked or how masking was maintained. It also does not report the randomization procedure, allocation concealment, or an analysis plan. These gaps constrain assessment of potential bias and the intended statistical comparisons.

The primary endpoint is protocol completion, while the study’s stated broader motivation concerns acceptability, feasibility, PTSD, adherence, and HIV outcomes. The record does not provide a separate acceptability result, a medication pill-count or compliance result, or a detailed account of intervention delivery. Consequently, the posted completion result cannot stand in for all aspects of feasibility or for the other outcomes described in the study rationale.

Secondary comparisons are unadjusted, and the record does not report a multiplicity strategy. Their results should therefore be viewed cautiously. The record also does not report information needed to judge whether scale differences are clinically meaningful. These limitations concern what can be established from the registry record; they do not determine what may have been collected or analyzed outside it.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: CPT-L to Improve Outcomes for Individuals With HIV and PTSD — NCT05275842.
• Registry record last updated 2025-03-04; status last verified 2025-02.
• Results first posted 2025-03-04.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

NCT05275842 is a completed randomized, parallel-group study of CPT-L and Lifesteps among individuals with HIV and PTSD. The registry lists single masking and phase NA. It identifies protocol completion at the 6-week end-of-study visit as the primary endpoint.

Completion was recorded for 12 of the 20 participants in CPT-L and 17 of the 21 participants in Lifesteps. The unadjusted primary comparison has a p-value of 0.141, and its confidence interval includes zero. The result is compatible with uncertainty about the direction and size of the group difference.

Posted secondary results cover CAPS-5, PCL-5, and viral suppression; medication pill count or compliance is listed as an outcome, but its result is not reported in the registry record. Analysis populations, missing-data methods, multiplicity handling, and the original sample-size justification are not reported. The record supports a cautious description of completion and the posted secondary estimates, not a definitive conclusion about clinical benefit.